粒子群算法在地震定位中的应用

Dong-xue Han, Gai-yun Wang
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引用次数: 4

摘要

粒子群算法是一种基于群体智能的自适应优化算法。介绍了它在地震定位中的基本原理和方法。为了得到更准确的结果,目标函数为同一地震回波两个台站的观测走时与理论走时的残差平方和。与遗传算法在地震定位中的应用相比,粒子群算法在快速准确定位震源方面具有明显的优势。PSO可能对地震定位有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Particle Swarm Optimization to Seismic Location
The particle swarm optimization (PSO) is an adaptive optimization based on swarm intelligence. The basic principle and the method of it being used in seismic location were introduced. To get a more accurate result, the objective function is the residual square sum of the observational travel-time and theoretical travel-time of the same earthquake return two stations. Compared with Genetic Algorithm on Seismic Location, PSO, after numerous experiments, proved its distinct superiority to locate the hypocenter more quickly and accurately. PSO is potentially useful for seismic location.
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